Drs. Michael Bonner and Leyla Isik will join our department on January 1 and July 1, 2019, respectively. They are recruiting PhD students to begin working in their labs in Fall 2019. Applications will be accepted Sept. 2018 through Dec 15, 2018. [Cognitive Science PhD Admissions Webpage]
The Cognitive Neuroscience and Machine Learning Lab, directed by Dr. Michael Bonner, is recruiting graduate students to start in Fall 2019. Dr. Bonner’s lab combines methods from cognitive and computational neuroscience, computer vision, and natural language processing to understand how fundamental aspects of human cognition are implemented in the computational circuity of the brain. Current work in the lab is focused on questions in high-level visual perception and semantic cognition. For example, how do we make sense of complex, natural scenes? What computational processes allow for the remarkable flexibility and speed of human vision? How do semantic knowledge and common-sense reasoning contribute to natural perception?
The lab’s goal is to reverse engineer the algorithms that the brain uses to solve these problems. Dr. Bonner is seeking graduate students who are interested in developing research projects that address central questions at the intersection of neuroscience, cognitive science, and artificial intelligence. Graduate students who may be interested in developing collaborations or co-mentorships with other labs at JHU are also welcome. Applicants should have a strong interest in scientific programming and quantitative modeling. Prospective applicants should feel free to email Dr. Bonner to discuss potential projects and opportunities in the lab.
Dr. Leyla Isik is recruiting graduate students to join the Computational Cognitive Neuroscience Lab in Fall 2019. Dr. Isik’s lab investigates the neural basis of human visual and social perception using a combination of neuroimaging (fMRI, EEG, MEG, ECoG), computational modeling, and machine learning. For more information on the lab’s research, please visit isiklab.org.
Creative, self-motivated candidates from a variety of fields, including cognitive science, neuroscience, psychology, engineering, and computer science, are encouraged to apply. Applicants should have strong quantitative and computational skills. Experience with neuroimaging or behavioral experiments is also desired, but not required.